4 Ways to Introduce Artificial Intelligence to eCommerce

Over the past few years, public perception of Artificial Intelligence has split into two camps: on the one hand you’ve got AI’s flag-bearers - those who think it’ll shape humanity for the next hundreds of years.

They see it as an unstoppable force that, although not flawless, will make life easy by optimizing pretty much every way we interact with the world.

On the other hand there’s the people who just don’t trust AI. They say machines will end up turning into hyper-intelligent, runaway robots that will enslave humanity.

These commentators will perceive any advances in AI as a threat and will be far from first adopters.

It allows human intervention when desired, but in the meantime, it automatically offers relevant and personalized results to the customers that an enterprise has worked so hard to attract.

2. Personalize the Shopping Journey

Let’s take a moment to think about how most people shop offline (and what that digital equivalent is).

Take a grocery store for instance, some shoppers know exactly what they want and go directly to the right aisle (faceted navigation).

Some wander up and down the aisles, seeing what items catch their eye this time (creative merchandising). Other shoppers go directly to the attendant and ask for help (site search).

While in a physical store, with a few hundred shoppers per day and a limited number of products, a human staff can handle the needs of all visitors.

Online stores, with thousands of daily shoppers and even more products, need some additional help guiding their customers to the products they need.

AI enables personalization at scale, so customers find what they need quicker, are more satisfied with the experience, and businesses see a higher conversion rate.

Without any personalization, shoppers have to navigate a digital warehouse of thousands of products without knowing where to start, and retailers have to make blanket decisions for every shopper - even though we know no one has the same shopping list.

A lack of personalization leads to suboptimal outcomes for both the customer and the retailer:

Customers can’t find the products they really want

Customers buy products that don’t fit their needs as closely as they should and go for the ‘next best thing’

Customers end up not buying at all

Retailers have the time to only manually curate a few categories, leaving many products buried

Retailers leave money on the table by not showing relevant products - even when they have them

A person’s buying journey isn’t simply about running through a list of requirements and matching these to a product.

Less tangible things need to be taken into account, like tastes, trends and people’s never-ending search for novelty.

This is where the strength of combining a human touch with Artificial Intelligence in eCommerce comes into play.

3. Give Relevant Product Recommendations to Customers

Let’s have a look at an example of collaboration between human and machine.

One of the most impactful applications of Artificial Intelligence in eCommerce is bury and boost.

The basic idea behind it is that you show your customers products with certain characteristics - the products they’re likely to want to buy. At the same time, you hide products they’re less likely to be interested in.

But, how do you know which products should be boosted and which should be buried? How do you set the rules?

That’s where AI comes in to help. AI will constantly analyze all behavior from visitors - how they reach your website, where they click, what they buy, etc…

It will consider the individual visitor, but will also take into account the wisdom of the crowd that it’s learned from all visitors.

This way it creates an in-depth picture of what an individual visitor is likely to be most interested in.

Take the example of Halfords. They optimized their site search using AI. Every time someone visits the website, the AI starts analyzing their behavior and predicts what they might want to buy.